nuTonomy CEO and co-founder Karl Iagnemma says the challenge of adapting autonomous drive systems to diverse road rules globally is a barrier to any single company dominating self-driving tech.

Karl Iagnemma, like founding members of Google’s self-driving car team, has worked to perfect autonomous vehicle technology since the U.S. Defense Department’s DARPA Challenge robot vehicle races a decade ago. Joined by co-founder (and MIT DARPA Challenge teammate) Emilio Frazzoli, the two created Cambridge, Massachusetts-based nuTonomy in 2013 to commercialize research they’d pursued as MIT roboticists.

Though overshadowed to some extent by Google and its Waymo self-driving car unit and Uber’s aggressive push for autonomous vehicle dominance, nuTonomy has nevertheless established itself as a player in the nascent technology. It launched the first public driverless taxi test program in Singapore last year, followed by a pilot program in Boston with ridehailing firm Lyft and a tech alliance with French automaker Peugeot. It’s raised just $20 million so far, but CEO Iagnemma tells Forbes that technical knowhow and strategic alliances may be more important at this stage than cash.

He shared his views on the state of the technology and challenges in adapting autonomous vehicle systems to different global regions in a recent interview.

Forbes: There’s been so much activity in the self-driving tech in the past two years. Where do things stand right now?

Iagnemma: “As an industry we've really progressed through a few different phases. The first phase, to be totally honest, was to just get these cars to drive around the block – convince ourselves that the technology could work as a proof of concept.

“We're beyond that stage. We're in what I would call a pre-validation stage. Validation means we've convinced ourselves that the software works well enough to put on the road without a driver. We're not quite there yet as an industry, but we're getting pretty close. That's why you've got Google putting a lot of cars on the road; that's why you have nuTonomy building up its fleet and logging a lot of kilometers, etc.

“Then the next stage, the one that's really interesting, is scaling the technology from one city to many cities. If you develop a technology that only works in a single city, where it's kind of optimized for a specific city, that's not really that exciting. The fact is, one of the dirty little secrets I would say, is that the software today is pretty city- or country-specific.”

Forbes: Why is that?

Iagnemma: “One of the obvious reasons is driving in different cities is a distinct experience. Some of the rules of the road, the appearance of the signage, the road markings are different. So when you move to a new city, you've got to adapt your software to drive in that location. …

“I think we sometimes think that once one company gets the technology right then overnight we'll have autonomous cars on the road in every major city worldwide. But in fact that's not the case. It's going to be a city-by-city, country-by-country rollout of this technology, which is going to take some time. …

“It's not just the rules of the road. There are cultural differences as well. In Singapore drivers generally obey the rules, but the attitude around pedestrians is actually quite different. It's culturally different. People drive safely, but it's not the same deference shown to pedestrians.

“Depending on how you develop your software, adapting your code to go from one market to the next, it could be a fairly painless process or it could be quite challenging and could require overhauling the code.

“Nobody really wants to hear that because with all the money they are spending on this technology they want to believe they have a global solution at their fingertips. That may not be the case.”

Forbes: So what does that mean for competition for autonomous tech leadership?

Iagnemma: “There's this whole notion of a race and a race usually implies one winner. I don't believe there will be a single winner in this space. It's such a huge market. It's a global opportunity.

“The fact that there are so many regional-specific elements at play, what that means is I think we're going to see the emergence of multiple winners per region.

“The group that gets to market first in North America may have a great advantage in North America but that may not give them any advantage at all in Asia. There may be another party that actually has a solution that comes to market a little later, but it's first in Asia. They may establish a dominant presence there, a very strong presence there."

Iagnemma: “I believe it's exactly the opposite when we look at a deep-learning based approach. The promise of that approach is that we can teach the car how to drive by feeding it many, many examples of good driving behavior.

“If we believe that's true those examples, if you're driving in the United States are really not very useful when you're in Singapore. In fact, they'll put you on the wrong side of the road.

“My point is that when you enter a new market and that market has different rules and a market has different appearances the burden on a learning-based approach may even be higher than an alternative approach because you may have to effectively retrain, if not from scratch, nearly from scratch.”

Forbes: What do you consider a better approach?

Iagnemma: “Think about a more flexible architecture where you've got a more systematic way of enforcing rules of the road.

“So when you go to new market in this more flexible manner let's say you can alter, reprioritize or modify some of these rules and just much more quickly adapt to those different driving conditions. That type of architecture in the long run could be a huge benefit when you think about scaling.

“The deep-learning question is really interesting. The promise is really appealing, where groups will say we'll cut through all the complexity by just teaching the car how to drive. I think there's some significant potential pitfalls there when we think about scalability.”

Forbes: What about taking an open-source approach to developing self-driving software?

Iagnemma: “It's interesting and I think the ambition is to be commended. I think there are challenges there in a few dimensions.

“In the automotive domain, generally speaking, when you look at consortium models, the groups that have leading technology are less incentivized to contribute to the consortia. There's a potential end state where you have participants that are not market leaders. And with a large field of participants that aren't leaders, there's no guarantee that just by combining resources they'll end up with a winning solution.

“It really does come down to the quality of the participants.

“Beyond that, I think it really raises some interesting and unresolved issues around liability. When you contribute to an open-source or a shared solution and there's a liability issue that arises from the use of that solution how will this be tracked back to individual contributors?

“I don't know the answer to that, but it's one that will be faced sooner or later in these types of models.”

Forbes: As autonomous fleets on public roads grow, there’s also a surge in startups touting new ideas for self-driving car for vision systems and sensors. Are the current options inadequate?

Iagnemma: “It speaks to the broader narrative that as an industry we're kind of sewing the parachute on the way down.

“We're developing the technology; we're putting in place the partnerships; we're making plans to go to market. But some of these key components and some of the technical solutions still have some wrinkles that need to be ironed out.”

nuTonomy

Self-driving Renault Zoe hatchbacks operated by nuTonomy go into service in Boston in a test program with Lyft this year.